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LDPolypVideo Benchmark
A large-scale colonoscopy video dataset containing diverse polyps. -
Hyperkvasir and LDPolypVideo
A large-scale colonoscopy video dataset containing 61 normal videos and 102 abnormal videos for training, and 30 normal videos and 60 abnormal videos for testing. -
Real-world anomaly detection in surveillance videos
Real-world anomaly detection in surveillance videos. -
Point Cloud Video Anomaly Detection Based on Point Spatio-Temporal Auto-Encoder
Video anomaly detection has great potential in enhancing safety in the production and monitoring of crucial areas. Currently, most video anomaly detection methods are based on... -
Abnormal Event Detection at 150 FPS in MATLAB
Abnormal Event Detection at 150 FPS in MATLAB dataset -
Street Scene
A new large-scale dataset for video anomaly detection, Street Scene, contains 46 training video sequences and 35 testing video sequences taken from a static USB camera looking... -
UCSD Ped1 & Ped2
UCSD Ped1 & Ped2 dataset for single-scene video anomaly detection -
Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomal...
Anomalies are rare and anomaly detection is often therefore framed as One-Class Classification (OCC), i.e. trained solely on normalcy. Leading OCC techniques constrain the... -
UCF-Crime and XD-Violence datasets
The UCF-Crime and XD-Violence datasets are used for weakly supervised video anomaly detection. -
Object-centric auto-encoders and dummy anomalies for abnormal event detection...
Object-centric auto-encoders and dummy anomalies for abnormal event detection in video. -
Clustering driven deep autoencoder for video anomaly detection
Clustering driven deep autoencoder for video anomaly detection. -
Learning Not to Reconstruct Anomalies
Video anomaly detection is often seen as one-class classification (OCC) problem due to the limited availability of anomaly examples. -
CUHK Avenue dataset
A benchmark dataset for anomaly detection in videos -
Video Anomaly Detection by Estimating Likelihood of Representations
Video anomaly detection is a challenging task not only because it involves solving many sub-tasks such as motion representation, object localization and action recognition, but... -
Video Anomaly Detection via Spatio-Temporal Pseudo-Anomaly Generation
Video Anomaly Detection (VAD) is an open-set recognition task, which is usually formulated as a one-class classification (OCC) problem, where training data is comprised of... -
ShanghaiTech
The ShanghaiTech dataset includes 330 training and 107 test videos recorded at 13 different background locations. -
CUHK Avenue
The CUHK Avenue dataset comprises one scene captured by a camera looking at an avenue near a subway entrance from a nearly horizontal view angle.
